TY - JOUR
T1 - Correction of technical bias in clinical microarray data improves concordance with known biological information
AU - Eklund, Aron Charles
AU - Szallasi, Zoltan Imre
PY - 2008
Y1 - 2008
N2 - The performance of gene expression microarrays has been well characterized using controlled reference samples, but the performance on clinical samples remains less clear. We identified sources of technical bias affecting many genes in concert, thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables. We developed a method to correct for technical bias in clinical microarray data, which increased concordance with known biological relationships in multiple data sets.
AB - The performance of gene expression microarrays has been well characterized using controlled reference samples, but the performance on clinical samples remains less clear. We identified sources of technical bias affecting many genes in concert, thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables. We developed a method to correct for technical bias in clinical microarray data, which increased concordance with known biological relationships in multiple data sets.
U2 - 10.1186/gb-2008-9-2-r26
DO - 10.1186/gb-2008-9-2-r26
M3 - Journal article
C2 - 18248669
VL - 9
SP - R26
JO - Genome Biology (Online Edition)
JF - Genome Biology (Online Edition)
SN - 1474-7596
IS - 2
ER -